A User Incentive-Based Scheme Against Dishonest Reporting in Privacy-Preserving Mobile Crowdsensing Systems

Proliferating Mobile Crowdsensing Systems (MCSs) is a promising paradigm to realize large-scale sensing targets in an agile and economical manner. Privacy protection mechanisms, which alleviate mobile user’s concern on participating MCS tasks, also introduce the issue of data quality to the MCS server. In privacy-preserving MCSs, dishonest reporting of mobile sensing data from task participants could severely affect the MCS sensing accuracy. In this paper, we develop a user incentive-based scheme against dishonest reporting in privacy-preserving MCSs. Our proposed scheme is capable of improving the MCS sensing accuracy by encouraging users to honestly upload obtained sensing information for a higher serving profit. The performance of our scheme is evaluated via extensive real-world trace-driven simulations. Our experimental results show that our scheme can effectively ensure MCS sensing accuracy while encouraging honest reporting.